scholarly journals Composite Indices Using 3 or 4 Components of the Core Data Set Have Similar Predictive Ability to Measure Disease Activity in RA: Evidence from the DANCER and REFLEX Studies

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Martin J. Bergman ◽  
William Reiss ◽  
Carol Chung ◽  
Pamela Wong ◽  
Adam Turpcu
Keyword(s):  
Clinical Trials ◽  
Assessment Tool ◽  
Predictive Ability ◽  
Disease Assessment ◽  
Control Treatment ◽  
Routine Practice ◽  
Data Set ◽  
Study Objective ◽  
Core Data ◽  
Composite Indices

Background. Understanding how disease-assessment indices perform in rheumatoid arthritis (RA) clinical trials can inform their use in routine practice. The study objective was to assess the capacity of combinations of RA Core Data Set measures to distinguish rituximab from control treatment.Methods. Post hoc analysis of two randomised clinical trials was used. Composite Efficacy Indices were derived by combining three or four RA Core Data Set measures from three possible sources: physician, patient, and laboratory.Results. All 105 Composite Efficacy Indices evaluated significantly distinguished rituximab from control treatment (P<10−7). Generally, indices containing measures from three different sources had a greater capacity to distinguish rituximab from control treatment than indices containing three measures from one source. Composite Efficacy Indices performed as well as validated indices such as DAS28, RAPID3, and CDAI.Conclusions. All indices composed of three or four RA Core Data Set measures have a similar capacity to detect treatment differences. These results suggest that the precise measurement used is less important than whether any measurement is performed, although selection should be consistent for each patient. Therefore, the choice of assessment tool should not be limited to a prescribed list and should instead be left to the clinician’s discretion.

DETECTING TREATMENT GROUP DIFFERENCES IN ALZHEIMER’S DISEASE CLINICAL TRIALS: A COMPARISON OF ALZHEIMER’S DISEASE ASSESSMENT SCALE - COGNITIVE SUBSCALE (ADAS-COG) AND THE CLINICAL DEMENTIA RATING - SUM OF BOXES (CDR-SB)

2018 ◽  
pp. 1-6
Author(s):  
A.M. Wessels ◽  
S.A. Dowsett ◽  
J.R. Sims
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Treatment Group ◽  
Assessment Tool ◽  
Disease Assessment ◽  
Group Differences ◽  
Original Form ◽  
Clinical Dementia Rating ◽  
Cognitive Subscale

The Alzheimer’s Disease Assessment Scale’s cognitive subscale (ADAS-Cog) has been widely used as an outcome measure in Alzheimer’s Disease (AD) clinical trials. In its original form (ADAS-Cog11), the scale has been used successfully in mild-to-moderate AD dementia populations, but its use is more limited in the study of earlier disease (mild cognitive impairment [MCI] or mild dementia due to AD) owing to lack of appropriate sensitivity of some items. With recent focus on earlier treatment, efforts have focused on the development of more sensitive tools, including the Clinical Dementia Rating-Sum of Boxes (CDR-SB), a global assessment tool to evaluate both cognition and function. The ability of the ADAS-Cog and CDR-SB to detect treatment group differences in the clinical trial environment has not been systematically studied. The aim of this analysis was to compare the utility of these tools in detecting treatment group differences, by reviewing study findings identified through advanced searches of clinicaltrials.gov and Ovid, and press releases and scientific presentations. Findings from placebo-controlled studies of ≥ 6m duration and enrolling >100 participants were included; reporting of both the ADAS-Cog and CDR-SB at endpoint was also a requirement. Of the >300 records identified, 34 studies fulfilled the criteria. There were significant placebo versus active drug group differences based on findings from at least one measure for 14 studies. The ADAS-Cog detected treatment differences more frequently than the CDR-SB. Based on these and previously published findings, the ADAS-Cog appears more useful than the CDR-SB in detecting treatment group differences.

scholarly journals Identification of acute respiratory distress syndrome subphenotypes de novo using routine clinical data: a retrospective analysis of ARDS clinical trials

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e053297
Author(s):  
Abhijit Duggal ◽  
Rachel Kast ◽  
Emily Van Ark ◽  
Lucas Bulgarelli ◽  
Matthew T Siuba ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Clinical Data ◽  
Distress Syndrome ◽  
Secondary Outcome ◽  
Data Set ◽  
Study Objective ◽  
Clinical Variables

ObjectivesThe acute respiratory distress syndrome (ARDS) is a heterogeneous condition, and identification of subphenotypes may help in better risk stratification. Our study objective is to identify ARDS subphenotypes using new simpler methodology and readily available clinical variables.SettingThis is a retrospective Cohort Study of ARDS trials. Data from the US ARDSNet trials and from the international ART trial.Participants3763 patients from ARDSNet data sets and 1010 patients from the ART data set.Primary and secondary outcome measuresThe primary outcome was 60-day or 28-day mortality, depending on what was reported in the original trial. K-means cluster analysis was performed to identify subgroups. Sets of candidate variables were tested to assess their ability to produce different probabilities for mortality in each cluster. Clusters were compared with biomarker data, allowing identification of subphenotypes.ResultsData from 4773 patients were analysed. Two subphenotypes (A and B) resulted in optimal separation in the final model, which included nine routinely collected clinical variables, namely heart rate, mean arterial pressure, respiratory rate, bilirubin, bicarbonate, creatinine, PaO2, arterial pH and FiO2. Participants in subphenotype B showed increased levels of proinflammatory markers, had consistently higher mortality, lower number of ventilator-free days at day 28 and longer duration of ventilation compared with patients in the subphenotype A.ConclusionsRoutinely available clinical data can successfully identify two distinct subphenotypes in adult ARDS patients. This work may facilitate implementation of precision therapy in ARDS clinical trials.

scholarly journals Minimal Residual Disease Assessment in Lymphoma: Methods and Applications

2017 ◽  
Vol 35 (34) ◽  
pp. 3877-3887 ◽  
Author(s):  
Alex F. Herrera ◽  
Philippe Armand
Keyword(s):  
Clinical Trials ◽  
Minimal Residual Disease ◽  
Residual Disease ◽  
Response Assessment ◽  
Response To Therapy ◽  
Detection Methods ◽  
Disease Assessment ◽  
Routine Practice ◽  
Advantages And Disadvantages ◽  
Minimal Residual

Standard methods for disease response assessment in patients with lymphoma, including positron emission tomography and computed tomography scans, are imperfect. In other hematologic malignancies, particularly leukemias, the ability to detect minimal residual disease (MRD) is increasingly influencing treatment paradigms. However, in many subtypes of lymphoma, the application of MRD assessment techniques, like flow cytometry or polymerase chain reaction–based methods, has been challenging because of the absence of readily detected circulating disease or canonic chromosomal translocations. Newer MRD detection methods that use next-generation sequencing have yielded promising results in a number of lymphoma subtypes, fueling the hope that MRD detection may soon be applicable in clinical practice for most patients with lymphoma. MRD assessment can provide real-time information about tumor burden and response to therapy, noninvasive genomic profiling, and monitoring of clonal dynamics, allowing for many possible applications that could significantly affect the care of patients with lymphoma. Further validation of MRD assessment methods, including the incorporation of MRD assessment into clinical trials in patients with lymphoma, will be critical to determine how best to deploy MRD testing in routine practice and whether MRD assessment can ultimately bring us closer to the goal of personalized lymphoma care. In this review article, we describe the methods available for detecting MRD in patients with lymphoma and their relative advantages and disadvantages. We discuss preliminary results supporting the potential applications for MRD testing in the care of patients with lymphoma and strategies for including MRD assessment in lymphoma clinical trials.

Core Data Necessary for Reporting Clinical Trials on Nutrition in Infancy

2014 ◽  
Vol 66 (1) ◽  
pp. 31-35 ◽  
Author(s):  
Berthold Koletzko ◽  
Mary Fewtrell ◽  
Robert Gibson ◽  
Johannes B. van Goudoever ◽  
Olle Hernell ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Infant Nutrition ◽  
Main Body ◽  
Data Set ◽  
Core Data ◽  
Confidential Data ◽  
Previous Proposal ◽  
Meta Analyses ◽  
Made In

This paper presents an updated and revised summary of the ‘core data set' that has been proposed to be recorded and reported in all clinical trials on infant nutrition by the recently formed Consensus Group on Outcome Measures Made in Paediatric Enteral Nutrition Clinical Trials (COMMENT). This core data set was developed based on a previous proposal by the European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) Committee on Nutrition in 2003. It comprises confidential data to identify subjects and facilitate contact for further follow-up, data to characterize the cohort studied and data on withdrawals from the study, and some additional core data for all nutrition studies on preterm infants. We recommend that all studies on nutrition in infancy should collect and report this core data set to facilitate interpretation and comparison of results from clinical studies, and of systematic data evaluation and meta-analyses. Editors of journals publishing such reports are encouraged to require the reporting of the minimum data set described here either in the main body of the publication or as supplementary online material. © 2014 S. Karger AG, Basel

scholarly journals Content and Criterion Validity of the Preliminary Core Dataset for Clinical Trials in Fibromyalgia Syndrome

2009 ◽  
Vol 36 (10) ◽  
pp. 2330-2334 ◽  
Author(s):  
ERNEST H. CHOY ◽  
LESLEY M. ARNOLD ◽  
DANIEL J. CLAUW ◽  
LESLIE J. CROFFORD ◽  
JENNIFER M. GLASS ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Outcome Measures ◽  
Outcome Measurement ◽  
Criterion Validity ◽  
Pooled Analysis ◽  
Data Set ◽  
Core Data ◽  
The Core ◽  
Related Quality ◽  
Convergent And Divergent Validity

Objective.Increasing research interest and emerging new therapies for treatment of fibromyalgia (FM) have led to a need to develop a consensus on a core set of outcome measures that should be assessed and reported in all clinical trials, to facilitate interpretation of the data and understanding of the disease. This aligns with the key objective of the Outcome Measures in Rheumatology (OMERACT) initiative to improve outcome measurement through a data driven, interactive consensus process.Methods.Through patient focus groups and Delphi processes, working groups at previous OMERACT meetings identified potential domains to be included in the core data set. A systematic review has shown that instruments measuring these domains are available and are at least moderately sensitive to change. Most instruments have been validated in multiple languages. This pooled analysis study aims to develop the core data set by analyzing data from 10 randomized controlled trials (RCT) in FM.Results.Results from this study provide support for the inclusion of the following in the core data set: pain, tenderness, fatigue, sleep, patient global assessment, and multidimensional function/health related quality of life. Construct validity was demonstrated with outcome instruments showing convergent and divergent validity. Content and criterion validity were confirmed by multivariate analysis showing R square values between 0.4 and 0.6. Low R square value is associated with studies in which one or more domains were not assessed.Conclusion.The core data set was supported by high consensus among attendees at OMERACT 9. Establishing an international standard for RCT in FM should facilitate future metaanalyses and indirect comparisons.

Validation and inter-rater reliability of inexpensive, mini, no-touch infrared surface thermometry devices as an assessment tool for prediction of wound-related deep and surrounding infection

WCET Journal ◽  
2019 ◽  
pp. 18-22
Author(s):  
Hiske Smart ◽  
Eman Al Al Jahmi ◽  
Ebrahim Buhiji ◽  
Sally-Anne Smart
Keyword(s):  
Temperature Difference ◽  
Assessment Tool ◽  
Predictive Ability ◽  
Skin Surface ◽  
Infrared Thermometry ◽  
Health Care Clinics ◽  
Primary Health ◽  
Wound Assessment ◽  
The Times ◽  
Assessment Modality

Industrial infrared thermometry devices are large and, despite being less expensive than the current gold standard Exergen Dermatemp medical infrared thermometer, are still not affordable enough to ensure unrestricted and consistent use of this assessment modality in regular wound-related day-to-day practice. An increased skin surface temperature differentiation of 3°F associated with a wound has a positive predictive ability to detect deep or surrounding wound infection. This study hypothesised that inexpensive, pen- or pocket-sized, no-touch surface infrared thermometry devices will be equal in ability to detect a 3oF increased skin temperature compared to the Exergen Dermatemp infrared device and be reliable in the hands of any wound assessor. The odds of the control and other thermometers to detect a 3oF temperature difference, irrespective of the raters, were achieved in all five of the mini thermometers tested, with a correct temperature difference prediction that occurred in 90.933% of the times (odds determined 9/10). As a result of this study mini, no-touch infrared thermometry, to detect a 3oF temperature difference in wound assessment to determine tendency, could be implemented into primary health care clinics, rural clinics, day-to-day hospital practice and standard outpatients departments at a small financial cost, regardless of which thermometer is put to use.

A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials

2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Latent Variable ◽  
Brain Regions ◽  
Disease Assessment ◽  
Latent Variable Analysis ◽  
The Relationship ◽  
Selection Of

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.

scholarly journals Calling for improved quality in the registration of traditional Chinese medicine during the public health emergency: a survey of trial registries for COVID-19, H1N1, and SARS

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhuoran Kuang ◽  
◽  
Xiaoyan Li ◽  
Jianxiong Cai ◽  
Yaolong Chen ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Secondary Outcome ◽  
Specific Information ◽  
Clinical Trial Registry ◽  
Data Set ◽  
Diagnosis Criteria

Abstract Objective To assess the registration quality of traditional Chinese medicine (TCM) clinical trials for COVID-19, H1N1, and SARS. Method We searched for clinical trial registrations of TCM in the WHO International Clinical Trials Registry Platform (ICTRP) and Chinese Clinical Trial Registry (ChiCTR) on April 30, 2020. The registration quality assessment is based on the WHO Trial Registration Data Set (Version 1.3.1) and extra items for TCM information, including TCM background, theoretical origin, specific diagnosis criteria, description of intervention, and outcomes. Results A total of 136 records were examined, including 129 severe acute respiratory syndrome coronavirus 2 (COVID-19) and 7 H1N1 influenza (H1N1) patients. The deficiencies in the registration of TCM clinical trials (CTs) mainly focus on a low percentage reporting detailed information about interventions (46.6%), primary outcome(s) (37.7%), and key secondary outcome(s) (18.4%) and a lack of summary result (0%). For the TCM items, none of the clinical trial registrations reported the TCM background and rationale; only 6.6% provided the TCM diagnosis criteria or a description of the TCM intervention; and 27.9% provided TCM outcome(s). Conclusion Overall, although the number of registrations of TCM CTs increased, the registration quality was low. The registration quality of TCM CTs should be improved by more detailed reporting of interventions and outcomes, TCM-specific information, and sharing of the result data.

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